We validate the effectiveness of our Voxel-MAE with popular 3D object detectors, such as SECOND [1]}, CenterPoint [2]}, and PV-RCNN [3]} on two widely used autonomous driving datasets, KITTI [4]}, Waymo [5]}. As large-scale point clouds in autonomous driving are information redundant data, Voxel-MAE with even a 90% masking ratio can still learn representative features and improve the performance of 3D object detection. We also validate the effectiveness of Voxel-MAE in unsupervised domain adaptative 3D object detection, which proves the generalization ability of our Voxel-MAE in representation learning.
